Computed tomography systems have been proven in a plurality of applications and are capable of creating desired image information for the respective application. To improve the quality of the image information and to open up new applications projection or imaging information which has been created on the basis of a first spectral distribution of x-ray radiation and a second spectral distribution differing therefrom is frequently used. The terms dual-energy measurement or also multi-energy measurement are used in this context if two or more different spectral distributions are used. A spectral distribution is often abbreviated to “x-ray energy” or “hardness” of the x-ray radiation, since the average energy of the x-ray quanta is indeed produced or changes with the spectral distribution. In such cases the position of the energy maximum of the spectral distribution is generally specified as the value of the x-ray energy. A voltage, mostly in kV, is typically specified as the unit of measure.
A difficulty in such cases is selecting the first and second spectral distributions or energies of the x-ray radiation so that desired image information can be created from the projection information for the respective application. For example the desired image information can be based on a specific medical task or problem. The task can for example include bone structures being removed from the completed CT image (bone removal), of contrast medium information being removed from the completed CT image (virtual non-contrast), of specific crystalline deposits in tissue being recognizable for detecting gout in the completed CT image (gout) or that the extent of a lung embolism can be analyzed (lung dual-energy). In addition it can be necessary—not just in multi-energy operation—to also adapt the spectral distributions used to the examination object, if for example specific anatomical features of the examination object or patient require this.
It is precisely for the adaptation of x-ray energy to the anatomical features of the examination object that the operator of the imaging system needs to have an enormous amount of experience in order to determine the optimum control parameters for creating the desired image information. For example boundary conditions in respect of the radiation dose of the patient are to be taken into account in this process. Therefore a series of methods is known which automates the adaptation of the operating parameters of a computed tomography system or supports it semi-automatically. For multi-energy CT recordings this task is accordingly more difficult.